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Integral operator quality from low order interpolation
Sometimes nearest neighbor beats linear interpolation

Stewart A. Levin


In most discussions of interpolation methods, it is the worst-case behavior that dominates the analysis. From a systems point of view, one really should analyze how that interpolation is used in producing an end product in order to determine the interpolation's suitability. In this report I look at the summation operators slant stack, NMO and Kirchhoff migration as the ``systems'' and determine that their output quality can be significantly better than the traditional take on interpolation would suggest. In one scenario, I even found nearest neighbor interpolation did the job even better than linear interpolation.